An assessment of generative artificial intelligence in responding to clinical queries on tapering antidepressants

Generative AI is having a transformative impact on healthcare, including how healthcare professionals and patients access information about clinical queries, such as antidepressant tapering. The study findings show that GPT-4 was able to provide relevant and safety-conscious responses on antidepressant tapering. However, performance issues such as inconsistencies and inaccuracies in tapering recommendations highlight the important role that healthcare professionals continue to play in providing patients with clinically trained, professional support in safely managing health-related issues. Further research on developing AI evaluation tools is needed to ensure consistency in the approaches used in evaluating the performance of AI in addressing clinical queries.

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Publication Details

Journal
Research in Social and Administrative Pharmacy
Published
2025-06-24
DOI
https://doi.org/10.1016/j.sapharm.2025.06.107
Citations
2
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
4.96

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article

An assessment of generative artificial intelligence in responding to clinical queries on tapering antidepressants

Cathal Cadogan, Martinez Oscar, Miriam Boland
2 citations
Research in Social and Administrative Pharmacy
Machine Learning in Healthcare
4.96
article

An assessment of generative artificial intelligence in responding to clinical queries on tapering antidepressants

Cathal Cadogan, Martinez Oscar, Miriam Boland
article en
2 citations

Abstract

Generative AI is having a transformative impact on healthcare, including how healthcare professionals and patients access information about clinical queries, such as antidepressant tapering. The study findings show that GPT-4 was able to provide relevant and safety-conscious responses on antidepressant tapering. However, performance issues such as inconsistencies and inaccuracies in tapering recommendations highlight the important role that healthcare professionals continue to play in providing patients with clinically trained, professional support in safely managing health-related issues. Further research on developing AI evaluation tools is needed to ensure consistency in the approaches used in evaluating the performance of AI in addressing clinical queries.

Research in Social and Administrative PharmacyVol. 21(11)
Trinity College Dublin (IE)
Trinity College Dublin
Openalex Percentile: Top 5%
Machine Learning in Healthcare
4.96
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An assessment of generative artificial intelligence in responding to clinical queries on tapering antidepressants — Cathal Cadogan, Martinez Oscar, et al. · Research in Social and Administrative Pharmacy (2025) | TGRS Research Map | TGRS